Scenarios

1. Introduction

Scenarios are narratives of possible futures, depicting divergent visions of what the future may hold and providing insights when evaluated of potential outcomes for nature and society.

Scenarios capture different decisions and policy options being considered by multiple partners working and living in a region.

Scenarios are then translated by models into consequences for nature, nature’s benefits to people and quality of life (IPBES 2016).

Current drives of biodiversity loss and environmental degradation have promoted the evaluation of multiple scenarios that are usually of global scale concern (top-down approaches), such as climate change and land cover and land use change. Multilateral agencies have developed global narratives to help inform global targets and national policies.

In contrast with this top-down approach, participatory scenarios (bottom-up approaches) emerge to respond to local communities’ specific needs, realities and expectations.  Aligning and integrating top-down and bottom-up approaches, that is plausible global and local narratives and their interactions, is an ongoing challenge.

There is also a trend to create explicit narratives for biodiversity and ecosystem services or at least include their story-lines within scenario evaluation.

Before describing global, participatory and narrative for biodiversity and ecossytem services, let’s present four different types of scenarios proposed by IPBES (2016) (Figure below). Although these types of scenarios are proposed under the umbrella of top-down approaches, it can also help participatory scenario planning.

  • Exploratory scenarios examine a range of plausible futures, contributing to high level-level problem identification and agenda setting. For instance, socio-economic scenarios are a common starting point to explore plausible futures for biodiversity, ecosystem services and human well-being.

  • Intervention scenarios evaluate alternative policy or management, contributing to policy design and implementation. There are two classes of intervention scenario:

    • Target-seeking scenarios: there is agreement on a common target but there are alternative pathways to get there  (e.g., exploring structural changes in production and consumption to reduce biodiversity loss, Netherlands Environmental Assessment Agency 2010).

    • Policy-screening scenarios: evaluate several available policy instruments in moving towards specific targets or goals.

  • Retrospective policy evaluation (also known as “ex-post evaluation”), the  observed trajectory of a policy implemented in the past is compared to scenarios  that would have achieved the intended target.

Note: The Integrated Assessment Modeling Consortium has coordinated several processes to collect quantitative integrated assessment scenarios from the research community.

The roles played by different types of scenarios corresponding to the major phases of the science-policy cycle. Four types of scenarios are illustrated by graphs of changes in nature and nature’s benefits over time. The four major phases of the policy cycle are indicated by the labels and grey arrows outside the coloured quarters of the circle. In “exploratory scenarios”, the dashed lines represent different plausible futures, often based on storylines. In “target-seeking scenarios” (also known as “normative scenarios”), the diamond represents an agreed-upon future target and the coloured dashed lines indicate scenarios that provide alternative pathways for reaching this target. In “policy-screening scenarios” (also known as “ex-ante scenarios”), the dashed lines represent various policy options under consideration. In “retrospective policy evaluation” (also known as “ex-post evaluation”), the observed trajectory of a policy implemented in the past (solid black line) is compared to scenarios that would have achieved the intended target (dashed line). (Source: IPBES 2016)

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2. Drivers of change

This section is under construction!

Climate change Land-cover and land use change

3. Global scenarios

“Scenarios capture different policy options being considered by decision makers, which are then translated by models into consequences for nature, nature’s benefits to people and quality of life” (IPBES 2016).

IPBES (2016) described four different types of scenarios (Table below) and proposes an approach to use scenarios and models to assess uncertainties in future outcomes required to inform the four stages of the policy cycle.

Categories of scenario types as described by IPBES (2016)

Scenario type Aim Summary Examples
Exploratory (descriptive) To support agenda setting Examines a range of plausible futures, based on potential trajectories of drivers – either indirect (e.g., socio-political, economic and technological factors) or direct (e.g., habitat conversion and climate change)

Millennium Ecosystem Assessment

Global Environmental Outlook (GEO)

OpenNESS

United Kingdom National Ecosystem Assessment

Target-seeking (normative) To support policy design It examines the viability and effectiveness of alternative pathways to the desired outcome.

Roads from Rio +20: Pathways to achieve global sustainability goals by 2020

VOLANTE European VISIONS on sustainable land use

Policy screening (ex-ante) To support implementation A policy, or set of policies, is applied and an assessment of how the policy modifies the future is carried out

Rethinking Global Biodiversity Strategies (Ten Brink et al  2010)


Moser & Mußhoff 2015

Sarkki et al. 2022

Retrospective policy evaluation (ex-post) To support policy review

Qiu et al. 2020


3.1. Exploratory scenarios

“Exploratory scenarios” examine a range of plausible futures, contributing to high level-level problem identification and agenda setting. For instance, socio-economic scenarios are a common starting point to explore plausible futures for biodiversity, ecosystem services, and human well-being (Table below). 

Global Socio-Economic Scenarios.

Name Scenarios
Share Socio-economic Pathways (SSPs, IPCC 2021, see also description here)

Share Socioeconomic Pathways (SSPs)

  • SSP1. Sustainability

  • SSP2. Middle of the Road

  • SSP3. Regional rivalry

  • SPP4. Inequality

  • SPP5. Fossil fuel development

Representative Concentration Pathways (RCPs, CMIP6, earlier climate scenarios)

Moss et al. (2010), van Vuuren et al. (2011), Climate Change (2021); O’Neill et al. (2016); Meinshause et al. (2020).

  • RCP 2.6

  • RCP 4.5

  • RCP 6.0

  • RCP 7.0

  • RCP 8.5

The Millennium Ecosystem Assessment, 2005
  • Global Orchestration (globalized, with emphasis on economic growth and public goods),

  • Order from Strength (regionalized, with emphasis on national security and economic growth),

  • Adapting Mosaic (regionalized, with emphasis on local adaptation and flexible governance), and

  • TechnoGarden (globalized, with emphasis on green technology).

For example, Shared Socioeconomic Pathways (SSPs) are based on five plausible narratives describing alternative socio-economic developments (Riahi et al. 2017). SSPs include a range of scenarios drivers such as population, economic growth and urbanization, further use to develop integrated scenarios (baseline and mitigation), including energy systems, land-use change (Popp et al. 2017), air pollutants, greenhouse gas emissions and atmospheric concentrations (Riahi et al. 2017). Within these, SSP 2 “Middle of the Road” SSP 2 describes a world in which the human population peaks at 9.4 billion by 2070 and economic growth is moderate and uneven, while globalization continues with slow socio-economic convergence between countries.

Controlling future changes of land use

Recent research has used SSPs as a basis to assess single action vs. combined action scenarios for biodiversity recovery in the coming century (Leclère et al. 2020). Leclère et al. (2020) found that global terrestrial biodiversity trends caused by habitat conversion could be reversed if action was immediate, and of unprecedented ambition and coordination. This would be possible while still being consistent with the broader sustainability agenda, such as provisioning the food for the growing human population. The trends varied across the six biodiversity indicators they chose that were selected for their ability to project biodiversity metrics regionally and globally under various scenarios of spatially explicit future changes in land use. Their projections considered only the effect of future changes in land use, and did not account for future changes in other threats to biodiversity (for example, climate change, biological invasions or hunting).

Integrating regional climate change-biodiversity feedbacks

Recent research calls for more realistic scenarios that integrate regional climate change-biodiversity feedbacks (Cabral et al. 2023). One recent example is provided by Mori et al. (2021) who assessed the benefits of climate mitigation on global tree biodiversity (persistence and changes in distribution due to range shifts), and the benefits this would have for diversity dependent primary productivity and carbon storage by forests. They found that, in many biomes, climate change mitigation could substantially reduce the global loss of tree diversity that would otherwise be expected to result from an unabated climate change. This, in turn, is expected to reduce the loss of productivity that would otherwise be expected to result from biodiversity loss. Climate change mitigation is estimated to curtail productivity losses by approximately 9–39% compared with the baseline scenario of unabated warming. The alleviated loss of tree diversity and the resultant conservation of biodiversity-dependent productivity are especially substantial in colder and drier biomes compared with warmer and wetter biomes, probably because species in these biomes are often close to the edge of their climatic niche.

Reducing the adverse impacts of climate change on species in ecosystems is important, as they serve as a massive sink and storehouse of carbon, thereby contributing to climate stabilization (the desirable pathway to stabilizing feedback between climate change mitigation and biodiversity conservation. This scenario analysis reveals a triple win for climate, nature, and society by simultaneously protecting and leveraging the ecosystem benefits contributed by the biodiversity of the world’s forests.

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3.2. Target seeking scenarios

Global commitments to the GBF to protect 30% of land by 2030 present an opportunity to slow rates of biodiversity loss by protecting critical habitat and reducing extinction risk. Let’s see a couple of examples in this direction.

This section is under construction!

Eckert et al. (2023) explored a range of 30×30 conservation scenarios for Canada that varied the dimension of biodiversity prioritized (i.e. taxonomic groups, species-at-risk, biodiversity facets) and how protection is coordinated (transnational, national, or regional approaches) to test which decisions influence our ability to capture biodiversity in spatial planning. 

They evaluated how well each scenario captures biodiversity using scalable indicators while accounting for climate change, data bias, and uncertainty. They used spatial prioritization to test whether prioritizing different dimensions of biodiversity versus prioritizing at different spatial scales matters more for 30×30 biodiversity outcomes (Figure below). 

They first built species distribution models to project the current and future ranges of all Canadian terrestrial vertebrates, plants, and butterflies. To incorporate climate change, they down-weighted future projections to account for uncertainty and to prioritize “win-win” areas of overlap between current and future ranges. Next, they designed 30×30 expansion scenarios that varied the dimension of biodiversity (i.e., taxa, species at-risk, facets) to be prioritized and how well protection is coordinated spatially. Finally, to evaluate spatial prioritization scenarios, they quantify both the amount of biodiversity captured using weighted endemism as well as the number of species protected based on a modified Species Protection Index (SPI), where a species is considered protected when it reaches or exceeds its species-specific conservation target.

Conceptual workflow of methods used by Eckert et al. (2023) to prioritize protected areas in Canada to reach 30% by 2030 under different scenarios.

They found that only 15% of all terrestrial vertebrates, plants, and butterflies (representing only 6.6% of species-at-risk) are adequately represented in existing protected land in Canada. However, a nationally coordinated approach to 30×30 could protect 65% of all species representing 40% of all species-at-risk. How protection is coordinated has the largest impact, with regional approaches protecting up to 38% fewer species and 65% fewer species-at-risk, while the choice of biodiversity incurs much smaller trade-offs. These results demonstrate the potential of 30×30 planning in Canada while highlighting the critical importance of biodiversity-informed national strategies (Figure below).

(a) Spatial priorities for the optimal National scenario as well as the Transnational, Provinces & Territories, and Ecozones scenarios are highlighted in color based on their priority rank. (b) These shifting spatial priorities incurred high trade-offs across all elements of biodiversity. Trade-offs represent the loss of potential protection from the optimal national scenario. Trade-offs are calculated as the percentage difference between the amount of protection achieved by the alternative scenario and the amount of protection possible under the National scenario. For example, if the National scenario protects 80 species but the alternative scenario only protects 40 species, then the trade-off is −50% since the alternative scenario protects half as many species (from Eckert et al. 2023).

The same analyses were applied to Quebec (Eckert et al. 2023b) in an analysis for the MELCCFP of the Quebec government. At the provincial level, spatial priorities for biodiversity can be clustered into four main geographic groups, although there are areas of high priority across the province (Figure below). High priority clusters include the southern region of the province including parts of Les Appalaches, Basses-terres du Saint-Laurent, Les Laurentides méridionales, Basses-terres de l’Abitibi as well as the area around Lac Saint Jean (Graben du Saguenay), the northern region including parts of Monts de Puvirnituq, Plateau de Salluit, Basses-terres de Puvirnituq, and Monts Torngat, and a mid-latitude region encompassing parts of Plateau de la Sainte-Marguerite and Massif du lac Magpie. These high priority areas contain a disproportionate amount of biodiversity and the establishment of new protected land in the identified 30x30 priority areas could enable the adequate protection of over 45% of Québec’s species. Furthermore, the expansion of protected land in these high priority areas could confer adequate protection for ~30% of all at- risk species, species which are largely under protected by existing protected areas. This represents a substantial gain from Québec’s current state of biodiversity conservation.

Full rank map for Québec spatial prioritization with continuous cell ranking based on priority. Insets highlight different potential conservation corridors that capture areas of high biodiversity as potential candidate protected areas for protection. Image from Eckert et al. (2023b). Inset 1 includes areas on the eastern shore of James Bay (Basse-Terre du lac Duncan).

Given the predicted high impact of climate change on species ranges in Québec, the observed difference in current and future spatial priorities is expected (Figure below).

Combined (left), only current (middle) and only future (right) 2030 spatial priorities for Québec’s biodiversity produced by only using current or future species ranges as input into Zonation 5. Image from Eckert et al. 2023b.

Future priorities under climate change tend to shift northward towards cooler regions where Québec’s biodiversity is expected to shift into. Low-latitude priority regions are still high priority areas in future scenarios given the extremely high species richness in southern Québec ecosystems and the persistence of that richness into the future despite climate change. We see areas on the east coast of James Bay come out as high and highest priority in all three scenarios (Figure below).

National (federal) priority rank map for the Hudson Bay-James Bay Lowlands based on prioritization of all species (terrestrial vertebrates, plants, butterflies). Darker cells represent those with a higher conservation value to the protection of Canadian biodiversity at large. Black polygons represent existing protected areas, based on the Canadian Protected and Conserved Areas Database. This map is part of a nation wide analysis to inform Canada’s path to protecting 30% of its land by 2030 by Eckert et al. (2023) and is provided courtesy of Isaac Eckert and Dr. Laura Pollock.

4. Participatory scenarios

This section is under construction! While large-scale/global scenarios provide good general guidance, and may help elicit some underlying linkages between social, demographic and economic features on the one side and ecosystem level changes on the other side, small-scale/local scenarios can be very useful for exploring possible futures at the community level. Participatory scenarios usually involve selected local or regional actors, recognized representatives of communities, and members with a certain expertise. They are most valuable for supporting community involvement, enabling local stewardship, and giving communities an opportunity to contribute to setting their own targets and imagine their own futures in view of conservation issues, local livelihoods and national policies.

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5. Biodiversity and Ecosystem Services Scenarios

This section is under construction!

Global biodiversity scenarios (see Ferrier et al. 2016) are difficult to identify and are usually built using direct drivers of ecosystem change such as Climate Change (CC) and Land-Cover and Land-Use Change (LCLUC, see Titeux et al. 2016), known as model-based biodiversity scenarios (Pereira et al. 2010, Kim et al. 2018). For instance, Kim et al. (2018) argue that the role nature and biodiversity-specific policies in scenario storylines are limited, as follow: “...coarse spatial resolution, and land-use classes that are not sufficiently detailed to fully capture the response of biodiversity to land-use change”. This is exacerbated by the heterogeneity of models and their methodological approaches and the lack of harmonized metrics of biodiversity and ecosystem services (except for the global Land-Use Harmonization (LUH) project see Hurtt et al. 2020).

Ecosystem services scenarios (ESSs) are even more difficult to construct and have been explored under the Millennium Ecosystem Assessment, 2005 scenarios (Bennett et al. 2005). Thus, challenges remain in developing relevant global scenarios for biodiversity (Maurin et al. 2022) and ecosystem services (Rosa et al. 2019.)), although some initiatives have emerged to co-create positive futures for nature and people (Lundquist et al. 2021, IPBES 2023, Kim et al. 2023, Sarkki et al. 2023, O’Connor et al. 2021).

Intercomparison of biodiversity and ecosystem services models using harmonized scenarios (SSPs and RCPs; two major drivers: land use and climate, Kim et al. 2018) have shown important limitations to overcome.

Projected outcomes for biodiversity under different scenarios depend not only on the social and economic scenario but also on the choice of climate scenario and the type of biodiversity model used to project change (Thuiller et al. 2019). Biodiversity scenarios are not meant to predict the future state of a biodiversity variable precisely, but rather to project the range of possible futures to better understand uncertainties and alternative expectations for the future. 

Accounting for climate scenarios, representative concentration pathways (e.g., RCPs), along with land-use scenarios, allows for an assessment of biodiversity change under a wide range of possible futures. Thuiller et al. (2019) stressed the importance of the choice of biodiversity models. There are different types of biodiversity models to consider, but statistical Species Distribution Models (SDMs), are particularly widespread. Thuiller et al. (2019) found that different algorithms could lead to substantial variability in expected outcomes and the uncertainty associated with them, which may override even the choice of RCPs. This issue was long recognized in climate sciences where it is no longer appropriate to show projected climatic trends from a single Global Climate Model (GCM). Rather, ensembles of climate trajectories are provided to users for scenario comparison via data portals (e.g., CMIP5). 

The biodiversity modelling community needs to report and communicate the variability resulting from the different options in biodiversity models (e.g. SDMs, dispersal scenarios) and scenario-derived input data (e.g., RCP). Thuiller et al. (2019) urged that variabilities originating from modelling algorithms, input data, and external forces be assessed and reported for better to strengthen the science and improve the confidence in the scenario-based findings for decision-makers in exploring options for conservation action (e.g., placement of in situ measure and protected areas.

6. Workshop findings

GEO BON and Parks Canada convened a two-day workshop in Montreal (Oct 16-17, 2023) with primary knowledge holders from three main partners groups: GEO BON experts, regional experts and indigenous scholars and partners (e.g., Parks Canada, ECCC, Indigenous communities). Some of the main conclusions from this workshop were:

The IPBES (2016) framework explains how to combine models, scenarios and, weaving multiple knowledge systems to help partners working and living in the HJBL.

The Group on Earth Observations Biodiversity Observation Network (GEO BON) provides a framework to monitor biodiversity and ecosystem services and can guide the development and implementation of tools for monitoring. The Canadian Consortium for Arctic Data Interoperability (CCADI) provides ethically open, accessible, and comprehensive digital resources to the broadest possible audience of data users.

Existing initiatives in the area provide a firm foundation for future work. A bottom-up approach could support The Cree Geoportal as a main GeoHub and observatory for the HJBL. Other regional observatories could offer valuable operational experience in similar environments and challenges (e.g., The Alaska Arctic Observatory and Knowledge Hub, The Sustaining Arctic Observing Networks (SAON), The Pan-Arctic Observing System of Systems (Arctic PASSION), The Research Network Activities for Sustained Coordinated Observations of Arctic Change (RNA CoObs) that supports SAON).

BON-in-a-Box enables alignment of the stakeholder and rightsholder communities on priorities for biodiversity monitoring and the data and models needed to produce robust conclusions about the trends in different facets of biodiversity and ecosystem services. This focuses shared resources needed to execute those priorities and accelerates adoption of information about biodiversity change into decision support tools.

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7. Guidance for action

1. Key areas

  • Develop participatory approaches to identify Shared Socioeconomic  Pathways (SSPs) relevant to the HJBL and link them to local socioeconomic pathways (SSPs) (see Szetey et al. 2021 for an example in Australia, Japan Yoshikawa et al. (2022), and Frame et al. (2018) on how to adapt global SSPs for national and local scenarios).

  • Adapt global SSPs to national scenarios by downscaling narratives to national and subnational levels, creating similar narratives across scales, and improving regional applicability of SSPs through iterative participatory co-design or co-creation of consistent multi-sector scenarios.

  • Co-create regional and local scenarios by weaving multiple knowledge systems and collaborating with multiple partners in identifying their needs and expectations. And, ensure scenarios are consistent across scales (Kurniawan 2020).

  • Leverage community-based opportunities (Esmail et al. 2023) and maximize the mutual benefits of cooperation by integrating multiple actors and strategies (O’Bryan et al. 2023).

  • Build decision support through scenario-building led by local communities. For instance: How do fire, climate change, subsidence, drought, permafrost thaw, interact and to affect the region’s biodiversity and the people living there? What are the tipping points and boundaries where we expect big changes to occur?

  • Identify the role of multiple biodiversity and ecosystem services in the HJBL within the narrative of future scenarios (Rosa et al. 2019.)).

  • Include in these scenarios additional drivers of habitat degradation, species extinction risk, declines in the population abundances of species, and shifts in the distribution of species and biomes (Periera et al. 2024).

  • Ensure the representation of direct and indirect drivers in scenarios by increasing the resolution (temporal, spatial and thematic) of land-, freshwater-, and coastal-use change, climate change, and other drivers including pollution and invasive species as identified by traditional and Western Science.

Create working groups to:

  • Ensure that a weaving multiple knowledge systems is implemented in all tasks and initiatives involved in BON establishment (e.g., identifying needs and expectations from multiple partners working and living in the region on biodiversity, ecosystem services, etc.).

  • Deploy state of the art data collection and maintenance, including data as SpatioTemporal Asset Catalogs (STAC), identify spatial and taxonomic gaps, and tools for the design of sampling schemes (Maslen et al. 2023).

  • Implement models for causal attribution of natural and human drivers of biodiversity change and methods for comparison of the evidence supporting alternative causal models (Gonzalez et al. 2023).

  • Co-design monitoring schemes and models used for trend detection and attribution with all partners.

Support and enhance capabilities of the local observatories:

  • Identify what resources, technologies and capacities that are already available, and assess what is needed (logistics, training, operational, funding, etc) in terms of the value of information for decision support (Bennett et al. 2018).

Deploy an information system that integrates observations, models and tools into reproducible and open workflows that respect FAIR and CARE principles (e.g. Bon in a Box):

  • Connect top down with bottom up approaches to biodiversity observations.

  • Invite communities to contribute knowledge and indicator monitoring-based assessments.

2. Exploratory scenarios

  • There is a need to integrate regional data sets, not only on climate change, but also on multiple facets of biodiversity change and ecosystem services to scale up results scales relevant to policy (Mori et al. 2021, Stralberg et al. 2015).

  • We can also estimate how changes in biodiversity,  and other landscape metrics of heterogeneity (e.g., habitat heterogeneity), might affect changes in biomass (e.g., Dynamic Habitat Index) and other measures of ecosystem functioning (Isbell et al. 2017, Gonzalez et al. 2020).

3. Target seeking scenarios

Coordinating efforts across spatial scales confirms the critical need to evaluate national strategies for reaching global targets (e.g., protecting 30% of Earth’s land by 2030, 30x30) (Eckert et al. 2023).

  • Evaluating the relative contribution of the HJBL to 30x30 global and national targets is a priority. The Canadian approach developed by Eckert et al. (2023) and its implementation in Quebec (Eckert et al. 2023b) should guide further analyses and alternative scenarios for conservation action.

  • Scenarios comparing priority areas for biodiversity protection with other 30x30 criteria such as integrity, connectivity (Kukkala and Moilanen 2017, Albert et al. 2027, Carroll et al. (2018), ecosystem services and equitable governance (Franz 2021) should be implemented (Eckert et al. 2023).

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